Joint Independent Subspace Analysis: Uniqueness and Identifiability.

IEEE Transactions on Signal Processing（2019）

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摘要

This paper deals with the identifiability of joint independent subspace analysis (JISA). JISA is a recently-proposed framework that subsumes independent vector analysis (IVA) and independent subspace analysis (ISA). Each underlying mixture can be regarded as a dataset; therefore, JISA can be used for data fusion. In this paper, we assume that each dataset is an overdetermined mixture of several mu...

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关键词

Data integration,Random processes,Data models,Mathematical model,Brain modeling,Functional magnetic resonance imaging,Electrocardiography

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